Workload governance and placement control plane
Govern all your workloads on infrastructure you own.
Platform architecture
Whatever you already run
Workloads
If your team runs it, PhantomAgent can orchestrate it on infrastructure you control, with policy and audit built in.
CI/CD pipelines, AI agents, model inference, tool servers, deployments, batch jobs, and the services around them: bring the workloads you operate today. PhantomAgent connects them without rip-and-replace, and without locking you to one vendor, runtime, or environment.
CI/CD pipelines
GitHub Actions, GitLab CI, Jenkins, CircleCI, and the runners behind your builds.
AI agents & models
Agents, inference, and model runtimes, hosted APIs or self-hosted, across your environments.
Tool servers
MCP and other endpoints that agents, pipelines, and automated jobs call at runtime.
Platform services
Browsers, sandboxes, data jobs, and internal APIs that complete a pipeline or agent run.
Why enterprises need a control plane, not another AI vendor
Adoption outpaces value
Every new model, agent, and tool adds another line item. Teams ship AI faster than they can attribute spend or prove outcomes. Bills climb while visibility stays flat.
Vendor lock-in compounds
Managed AI services and GPU brokers tie you to their clouds, pricing, and roadmaps. Switching providers means rebuilding integrations, policies, and runbooks from scratch.
Governance cannot lag adoption
Platform teams need one neutral layer to define policy, place workloads on approved infrastructure, attribute cost to teams, and prove what ran where without outsourcing operations to another AI vendor.
PhantomAgent is the workload governance and placement control plane on infrastructure you control: cloud, on-prem, and customer-owned. Break lock-in, tie spend to outcomes, and keep adoption on a path that delivers value.
Platform
Platform capabilities
Platform
Platform capabilities
Workload orchestration
Provision and run models, agents, and AI services across AWS, Azure, GCP, Kubernetes, and on-prem.
Self-hosted model enablement
Run internally hosted models for sensitive workloads, cost control, compliance, and reduced vendor dependency.
Governance and policy control
Define who can use which models, tools, agents, and infrastructure, with policy enforcement built into the platform.
Cost visibility and spend control
Tie rising AI spend to teams, workloads, and outcomes so adoption drives value instead of opaque line items.
Failover and reliability
Route workloads across healthy infrastructure and reduce lock-in to a single provider, region, or AI service.
Auditability and security
Capture activity across models, agents, tools, and infrastructure so teams can prove what ran, where it ran, and what it accessed.
Deployment options
Enterprise-ready AI control plane
PhantomAgent is built for production: governed AI operations on cloud, on-prem, and customer-owned infrastructure. Start with an on-prem demo trial or deploy with an enterprise license.
Enterprise license
For platform, security, FinOps, and infrastructure teams running mission-critical AI workloads at scale.
Evaluate in your environments first, then scale to production across the infrastructure your security and platform teams already operate.
FAQ
Frequently Asked Questions
Answers for platform, security, and infrastructure teams evaluating a governed AI control plane.